Evidence map›Paper›PMID 39429485›Full record

ArticleChronic diseases and translational medicine2024

Stem cell secretome restore the adipo-osteo differentiation imbalance in diabetic dental pulp-derived mesenchymal stem cells.

Avinash Sanap, Kalpana Joshi, Supriya Kheur, Ramesh Bhonde

Abstract read
In one paragraph

Article in Chronic diseases and translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Diabesity and Oral Immunity: Exploring the Interconnection.Advances in experimental medicine and biology · 2026
    Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Avinash SanapRegenerative Medicine Laboratory, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth, Pimpri Pune India.ORCID 0000-0003-2535-0958
Kalpana JoshiDepartment of Biotechnology Sinhgad College of Engineering affiliated to Savitribai Phule Pune University Pune India.
Supriya KheurRegenerative Medicine Laboratory, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth, Pimpri Pune India.
Ramesh BhondeRegenerative Medicine Laboratory, Dr. D. Y. Patil Dental College and Hospital Dr. D. Y. Patil Vidyapeeth, Pimpri Pune India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mesenchymal stem cells (MSCs) from type 2 diabetes mellitus (T2DM) individuals exhibit increased adipogenesis and decreased osteogenesis. We investigated the potential of adipose tissue-derived MSCs (ADMSCs) secretome obtained from healthy individuals in restoring the tumor necrosis factor-α (TNF-α) mediated imbalance in the adipo/osteogenic differentiation in the dental pulp-derived MSCs obtained from T2DM individuals (dDPMSCs). Methods: dDPMSCs were differentiated into adipocytes and osteocytes using a standard cocktail in the presence of (a) induction cocktail, (b) induction cocktail + TNF-α, and (c) induction cocktail+ TNF-α + ADMSCs-secretome (50%) for 15 and 21 days resp. Differentiated adipocytes and osteocytes were stained by oil red O and alizarin red and analyzed by using ImageJ software. Molecular expression of the key genes involved was analyzed by using reverse-transcription polymerase chain reaction (RT-PCR). Results: Treatment of TNF-α augmented the adipogenesis (9571 ± 765 vs. 19,815 ± 1585 pixel, Conclusion: ADMSCs secretome from healthy individuals restore the TNF-α influenced differentiation fate of dDPMSCs and therefore can be explored for T2DM clinical management in the future.

Indexed as

differentiationmesenchymal stem cellsmicroenvironmentsecretometype 2 diabetes mellitus

Identifiers

PMID39429485
PMCPMC11483546

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.